[2603.21866] Tacit Knowledge Management with Generative AI: Proposal of the GenAI SECI Model

[2603.21866] Tacit Knowledge Management with Generative AI: Proposal of the GenAI SECI Model

arXiv - AI 3 min read

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Abstract page for arXiv paper 2603.21866: Tacit Knowledge Management with Generative AI: Proposal of the GenAI SECI Model

Computer Science > Artificial Intelligence arXiv:2603.21866 (cs) [Submitted on 23 Mar 2026] Title:Tacit Knowledge Management with Generative AI: Proposal of the GenAI SECI Model Authors:Naoshi Uchihira View a PDF of the paper titled Tacit Knowledge Management with Generative AI: Proposal of the GenAI SECI Model, by Naoshi Uchihira View PDF Abstract:The emergence of generative AI is bringing about a significant transformation in knowledge management. Generative AI has the potential to address the limitations of conventional knowledge management systems, and it is increasingly being deployed in real-world settings with promising results. Related research is also expanding rapidly. However, much of this work focuses on research and practice related to the management of explicit knowledge. While fragmentary efforts have been made regarding the management of tacit knowledge using generative AI, the modeling and systematization that handle both tacit and explicit knowledge in an integrated manner remain insufficient. In this paper, we propose the "GenAI SECI" model as an updated version of the knowledge creation process (SECI) model, redesigned to leverage the capabilities of generative AI. A defining feature of the "GenAI SECI" model is the introduction of "Digital Fragmented Knowledge", a new concept that integrates explicit and tacit knowledge within cyberspace. Furthermore, a concrete system architecture for the proposed model is presented, along with a comparison with prior...

Originally published on March 24, 2026. Curated by AI News.

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